RapidRMSD: rapid determination of RMSDs corresponding to motions of flexible molecules

Towards development of new antimalarial compounds through in silico and in vitro assays

Malaria is one of most widespread infectious disease in world. The antimalarial therapy presents a series of limitations, such as toxicity and the emergence of resistance, which makes the search for new drugs urgent. Thus, it becomes necessary to explore essential and exclusive therapeutic targets of the parasite to achieve selective inhibition. Enoyl-ACP reductase is an enzyme of the type II fatty acid biosynthetic pathway and is responsible for the rate-limiting step in the fatty acid elongation cycle. In this work, we use hierarchical virtual screening and drug repositioning strategies to prioritize compounds for phenotypic assays and molecular dynamics studies. The molecules were tested against chloroquine-resistant W2 strain of Plasmodium falciparum (EC50 between 330.05 and 13.92 µM). Nitrofurantoin was the best antimalarial activity at low micromolar range (EC50 = 13.92 µM). However, a hit compound against malaria must have a biological activity value below 1 µM. A large number of molecules present problems with permeability in biological membranes and reaching an effective concentration in their target's microenvironment. Nitrofurantoin derivatives with inclusions of groups which confer increased lipid solubility (methyl groups, halogens and substituted and unsubstituted aromatic rings) have been proposed. These derivatives were pulled through the lipid bilayer in molecular dynamics simulations. Molecules 14, 18 and 21 presented lower free energy values than nitrofurantoin when crossing the lipid bilayer.

Deep Local Analysis evaluates protein docking conformations with locally oriented cubes

MOTIVATION

With the recent advances in protein 3D structure prediction, protein interactions are becoming more central than ever before. Here, we address the problem of determining how proteins interact with one another. More specifically, we investigate the possibility of discriminating near-native protein complex conformations from incorrect ones by exploiting local environments around interfacial residues.

RESULTS

Deep Local Analysis (DLA)-Ranker is a deep learning framework applying 3D convolutions to a set of locally oriented cubes representing the protein interface. It explicitly considers the local geometry of the interfacial residues along with their neighboring atoms and the regions of the interface with different solvent accessibility. We assessed its performance on three docking benchmarks made of half a million acceptable and incorrect conformations. We show that DLA-Ranker successfully identifies near-native conformations from ensembles generated by molecular docking. It surpasses or competes with other deep learning-based scoring functions. We also showcase its usefulness to discover alternative interfaces.

AVAILABILITY AND IMPLEMENTATION

http://gitlab.lcqb.upmc.fr/dla-ranker/DLA-Ranker.git.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

TSP, a virulent Podovirus, can control the growth of Staphylococcus aureus for 12 h

Methicillin-resistant Staphylococcus aureus (MRSA) is a prevailing nosocomial pathogen that is increasingly isolated in community settings. It shows resistance against all beta-lactam drugs and has acquired mechanisms to resist other groups of antibiotics. To tackle this emerging issue of MRSA, there is an urgent need for antibiotic alternatives, and utilizing lytic bacteriophages is one of the most promising therapeutic approaches. In the present study, a lytic bacteriophage TSP was isolated from hospital wastewater against MRSA. The phage efficiently inhibited bacterial growth for up to 12 h at MOI of 1 and 10. TSP phage showed activity against various isolates of MRSA and MSSA, isolated from different clinical samples, with variable antibiotic susceptibility patterns. The bacteriophage TSP showed stability at varying temperatures (25 °C, 37 °C) and pH values (5–9), while its maximum storage stability was observed at 4 °C. It had a short latent period (20 min) and burst size of 103 ± 5pfu/infected cells. TSP genome sequence and restriction analysis revealed that its genome has a linear confirmation and length of 17,987 bp with an average GC content of 29.7%. According to comparative genomic analysis and phylogenetic tree,TSP phage can be considered a member of genus “P68viruses”. The strong lytic activity and short latent period in addition to its lytic nature makes it a good candidate for phage therapy against MRSA infections, if it proves to be effective in in-vivo studies.

Point-specific interactions of isovitexin with the neighboring amino acid residues of the hACE2 receptor as a targeted therapeutic agent in suppressing the SARS-CoV-2 influx mechanism

Objective:

Despite the development of several vaccines against severe acute respiratory syndrome coronavirus-2, the need for an additional prophylactic agent is evident. In recent in silico studies, isovitexin exhibited a higher binding affinity against the human angiotensin converting-enzyme 2 (hACE2) receptor than existing antiviral drugs. The research aimed to find out the point specificity of isovitexin for the hACE2 receptor and to assess its therapeutic potential, depending on the stability of the isovitexin–hACE2 complex.

Materials and Methods:

The pharmacokinetic profile of isovitexin was analyzed. The crystal structure of the hACE2 receptor and the ligand isovitexin were docked to form a ligand–protein complex following molecular optimization. To determine the isovitexin–hACE2 complex stability, their binding affinity, hydrogen bonding, and hydrophobic interactions were studied. Lastly, the root mean square deviation (RMSD), root mean square fluctuation, solvent accessible surface area, molecular surface area, radius of gyration (Rg), polar surface area, and principal component analysis values were found by simulating the complex with molecular dynamic (MD).

Results:

The predicted Lethal dose₅₀ for isovitexin was 2.56 mol/kg, with an acceptable maximum tolerated dose and no hepatotoxicity or AMES toxicity. Interactions with the amino acid residues Thr371, Asp367, Glu406, Pro346, His345, Phe274, Tyr515, Glu375, Thr347, Glu402, and His374 of the hACE2 protein were required for the high binding affinity and specificity of isovitexin. Based on what was learned from the MD simulation, the hACE2 receptor-blocking properties of isovitexin were looked at.

Conclusions:

Isovitexin is a phytochemical with a reasonable bioactivity and safety profile for use in humans, and it can potentially be used as a hACE2-specific therapeutic to inhibit COVID-19 infection.

Active site-specific quantum tunneling of hACE2 receptor to assess its complexing poses with selective bioactive compounds in co-suppressing SARS-CoV-2 influx and subsequent cardiac injury

Objective:

This research aims to study the target specificity of selective bioactive compounds in complexing with the human angiotensin-converting enzyme (hACE2) receptor to impede the severe acute respiratory syndrome coronavirus 2 influx mechanism resulting in cardiac injury and depending on the receptor’s active site properties and quantum tunneling.

Materials and Methods:

A library of 120 phytochemical ligands was prepared, from which 5 were selected considering their absorption, distribution, metabolism, and excretion (ADMET) and quantitative structure–activity relationship (QSAR) profiles. The protein active sites and belonging quantum tunnels were defined to conduct supramolecular docking of the aforementioned ligands. The hydrogen bond formation and hydrophobic interactions between the ligand–receptor complexes were studied following the molecular docking steps. A comprehensive molecular dynamic simulation (MDS) was conducted for each of the ligand–receptor complexes to figure out the values – root mean square deviation (RMSD) (Å), root mean square fluctuation (RMSF) (Å), H-bonds, Cα, solvent accessible surface area (SASA) (Ų), molecular surface area (MolSA) (Ų), Rg (nm), and polar surface area (PSA) (Å). Finally, computational programming and algorithms were used to interpret the dynamic simulation outputs into their graphical quantitative forms.

Results:

ADMET and QSAR profiles revealed that the most active candidates from the library to be used were apigenin, isovitexin, piperolactam A, and quercetin as test ligands, whereas serpentine as the control. Based on the binding affinities of supramolecular docking and the parameters of molecular dynamic simulation, the strength of the test ligands can be classified as isovitexin > quercetin > piperolactam A > apigenin when complexed with the hACE2 receptor. Surprisingly, serpentine showed lower affinity (−8.6 kcal/mol) than that of isovitexin (−9.9 kcal/mol) and quercetin (−8.9 kcal/mol). The MDS analysis revealed all ligands except isovitexin having a value lower than 2.5 Ǻ. All the test ligands exhibited acceptable fluctuation ranges of RMSD (Å), RMSF (Å), H-bonds, Cα, SASA (Ų), MolSA (Ų), Rg (nm), and PSA (Å) values.

Conclusion:

Considering each of the parameters of molecular optimization, docking, and dynamic simulation interventions, all of the test ligands can be suggested as potential targeted drugs in blocking the hACE2 receptor.

Biomolecular response to hour-long ultralow field microwave radiation: An effective coarse-grained model simulation

Various electronic devices, which we commonly use, radiate microwaves. Such external perturbation influences the functionality of biomolecules. In an ultralow field, the cumulative response of a molecule is expected only over a time scale of hours. To study the structural dynamics of biomolecules over hours, we adopt a simple methodology for constructing the coarse-grained structure of the protein molecule and solve the Langevin equation under different working potentials. In this approach, each amino acid residue of a biomolecule is mapped onto a number of beads, a few for the backbone, and few for the side chain, depending on the complexity of its chemical structure. We choose the force field in such a way that the dynamics of the protein molecule in the presence of ultralow radiation field of microvolt/nm could be followed over the time frame of 2 h. We apply the model to describe a biomolecule, hen egg white lysozyme, and simulate its structural evolution under ultralow strength electromagnetic radiation. The simulation revealed the finer structural details, like the extent of exposure of bioactive residues and the state of the secondary structures of the molecule, further confirmed from spectroscopic measurements [details are available in Phys. Rev. E 97, 052416 (2018)10.1103/PhysRevE.97.052416 and briefly described here]. Though tested for a specific system, the model is quite general. We believe that it harnesses the potential in studying the structural dynamics of any biopolymer under external perturbation over an extended time scale.

HOPMA: Boosting Protein Functional Dynamics with Colored Contact Maps

In light of the recent very rapid progress in protein structure prediction, accessing the multitude of functional protein states is becoming more central than ever before. Indeed, proteins are flexible macromolecules, and they often perform their function by switching between different conformations. However, high-resolution experimental techniques such as X-ray crystallography and cryogenic electron microscopy can catch relatively few protein functional states. Many others are only accessible under physiological conditions in solution. Therefore, there is a pressing need to fill this gap with computational approaches. We present HOPMA, a novel method to predict protein functional states and transitions by using a modified elastic network model. The method exploits patterns in a protein contact map, taking its 3D structure as input, and excludes some disconnected patches from the elastic network. Combined with nonlinear normal mode analysis, this strategy boosts the protein conformational space exploration, especially when the input structure is highly constrained, as we demonstrate on a set of more than 400 transitions. Our results let us envision the discovery of new functional conformations, which were unreachable previously, starting from the experimentally known protein structures. The method is computationally efficient and available at https://github.com/elolaine/HOPMA and https://team.inria.fr/nano-d/software/nolb-normal-modes.

Predicting Protein Functional Motions: an Old Recipe with a New Twist

Large macromolecules, including proteins and their complexes, very often adopt multiple conformations. Some of them can be seen experimentally, for example with x-ray crystallography or cryo-electron microscopy. This structural heterogeneity is not occasional and is frequently linked with specific biological function. Thus, the accurate description of macromolecular conformational transitions is crucial for understanding fundamental mechanisms of life's machinery. We report on a real-time method to predict such transitions by extrapolating from instantaneous eigen motions, computed using the normal mode analysis, to a series of twists. We demonstrate the applicability of our approach to the prediction of a wide range of motions, including large collective opening-closing transitions and conformational changes induced by partner binding. We also highlight particularly difficult cases of very small transitions between crystal and solution structures. Our method guarantees preservation of the protein structure during the transition and allows accessing conformations that are unreachable with classical normal mode analysis. We provide practical solutions to describe localized motions with a few low-frequency modes and to relax some geometrical constraints along the predicted transitions. This work opens the way to the systematic description of protein motions, whatever their degree of collectivity. Our method is freely available as a part of the NOn-Linear rigid Block (NOLB) package.

Controlled-advancement rigid-body optimization of nanosystems

In this study, we propose a novel optimization algorithm, with application to the refinement of molecular complexes. Particularly, we consider optimization problem as the calculation of quasi-static trajectories of rigid bodies influenced by the inverse-inertia-weighted energy gradient and introduce the concept of advancement region that guarantees displacement of a molecule strictly within a relevant region of conformational space. The advancement region helps to avoid typical energy minimization pitfalls, thus, the algorithm is suitable to work with arbitrary energy functions and arbitrary types of molecular complexes without necessary tuning of its hyper-parameters. Our method, called controlled-advancement rigid-body optimization of nanosystems (Carbon), is particularly useful for the large-scale molecular refinement, as for example, the putative binding candidates obtained with protein-protein docking pipelines. Implementation of Carbon with user-friendly interface is available in the SAMSON platform for molecular modeling at https://www.samson-connect.net. © 2019 Wiley Periodicals, Inc.

Analytical symmetry detection in protein assemblies. II. Dihedral and cubic symmetries

Protein assemblies are often symmetric, as this organization has many advantages compared to individual proteins. Complex protein structures thus very often possess high-order symmetries. Detection and analysis of these symmetries has been a challenging problem and no efficient algorithms have been developed so far. This paper presents the extension of our cyclic symmetry detection method for higher-order symmetries with multiple symmetry axes. These include dihedral and cubic, i.e., tetrahedral, octahedral, and icosahedral, groups. Our method assesses the quality of a particular symmetry group and also determines all of its symmetry axes with a machine precision. The method comprises discrete and continuous optimization steps and is applicable to assemblies with multiple chains in the asymmetric subunits or to those with pseudo-symmetry. We implemented the method in C++ and exhaustively tested it on all 51,358 symmetric assemblies from the Protein Data Bank (PDB). It allowed us to study structural organization of symmetric assemblies solved by X-ray crystallography, and also to assess the symmetry annotation in the PDB. For example, in 1.6% of the cases we detected a higher symmetry group compared to the PDB annotation, and we also detected several cases with incorrect annotation. The method is available at http://team.inria.fr/nano-d/software/ananas. The graphical user interface of the method built for the SAMSON platform is available at http://samson-connect.net.

Analytical symmetry detection in protein assemblies. I. Cyclic symmetries

Symmetry in protein, and, more generally, in macromolecular assemblies is a key point to understand their structure, stability and function. Many symmetrical assemblies are currently present in the Protein Data Bank (PDB) and some of them are among the largest solved structures, thus an efficient computational method is needed for the exhaustive analysis of these. The cyclic symmetry groups represent the most common assemblies in the PDB. These are also the building blocks for higher-order symmetries. This paper presents a mathematical formulation to find the position and the orientation of the symmetry axis in a cyclic symmetrical protein assembly, and also to assess the quality of this symmetry. Our method can also detect symmetries in partial assemblies. We provide an efficient C++ implementation of the method and demonstrate its efficiency on several examples including partial assemblies and pseudo symmetries. We also compare the method with two other published techniques and show that it is significantly faster on all the tested examples. Our method produces results with a machine precision, its cost function is solely based on 3D Euclidean geometry, and most of the operations are performed analytically. The method is available athttp://team.inria.fr/nano-d/software/ananas. The graphical user interface of the method built for the SAMSON platform is available athttp://samson-connect.net.